社会网络视角下的二语词汇语义网络研究  

A Study of L2 Lexical-semantic Networks from the Perspective of Social Network

作　　者：冯学芳 刘洁 Feng Xue-fang;Liu Jie(The School of Foreign Languages,Huazhong University of Science and Technology,Wuhan 430070,China)

机构地区：[1]华中科技大学外国语学院,武汉430070

出　　处：《外语学刊》2022年第5期93-103,共11页Foreign Language Research

基　　金：国家社科基金项目“中国学生英语词汇语义网络动态模型构建及应用研究”(18BYY214)的阶段性成果。

摘　　要：本研究从词汇关联学习观出发,通过词汇语义流利测试收集数据,建立二语词汇语义网络,然后用社会网络分析工具Ucinet对该网络进行Concor分析,将网络中的单词节点分成连接密度和中心度各异的模块。通过中心节点单词和高频产出单词的对比发现:(1)中心节点单词习得时间早、使用频率高,符合词汇的优先连接模型;(2)单词语义特征对于其在网络中的地位有重要影响;(3)网络方法不仅可以描述词汇之间关联互动情况,而且可以清晰显示词汇社会表征网络的核心系统和外围系统的构成;(4)节点单词分区结果可以直接应用于课堂词汇教学。该研究提供了从中观和微观层面研究词汇语义网络的新思路,有利于词汇网络结构分析和词汇教学的结合。Based on associative learning theory,this study collected data from a semantic fluency test to set up a L2 lexical-semantic network and conducted Concor analysis to this network with a social network analysis tool Ucinet.The results classified all the nodes into blocks of different density and centrality.The comparison of central words and words with high occurrence led to several findings.Firstly,the central words feature early learning and high frequency,which is consistent with the preferential attachment model of word acquisition.Secondly,the semantic features of words are crucial to their positioning in the lexical network.Thirdly,the network approach can not only demonstrate the relation between words but also clearly portray the two components of lexical social representation:the core system and the periphery system.Finally,the partitions of words can be applied to enhance classroom vocabulary teaching.This research innovatively analyzes the lexical-semantic network from the microscopic and mesoscopic perspectives and aim at combining the analysis results with vocabulary teaching.

关 键 词：关联学习 二语词汇语义网络 社会网络 语义流利度 词汇表征 核心与外围系统 

分 类 号：H319[语言文字—英语]